Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-nl4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-nl4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-nl4") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-nl4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-large-nl4: direct link, hf CLI and curl.
- Browser
- Download file 601 MB
-
https://huggingface.co/google/t5-efficient-large-nl4/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-large-nl4/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-large-nl4/resolve/main/flax_model.msgpack
601 MB
- Xet hash:
- 04776f79931138c87be7eb72f4dc22e4c30086c26c6c2e7a1c53f02a6817707e
- Size of remote file:
- 601 MB
- SHA256:
- 73990bec74170afe9914e5be3f8547b4dd17089b1514cabc02df3adf73447679
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